CRISPR Guide RNA Scoring Calculator

Enter your Target DNA Sequence, PAM Sequence, and Cas Protein into the CRISPR Guide RNA Scoring Calculator, then adjust GC Content and Thermodynamics weights to get an Efficiency Score, Melting Temperature, and Specificity Score.

Enter the target sequence where CRISPR will cut

0.3
01

Weight for GC content in scoring (0-1)

0.2
01

Weight for position-specific effects

0.4
01

Weight for thermodynamic stability

0.1
01

Weight for secondary structure penalties

Consider potential off-target binding sites

Results

Efficiency Score

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GC Content

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Melting Temperature

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Specificity Score

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Recommendation

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Score Components Breakdown

Frequently Asked Questions

What is a good efficiency score for CRISPR guide RNAs?

Scores above 7.5 indicate high efficiency gRNAs that are likely to perform well in experiments. Scores between 5-7.5 are moderate efficiency, while scores below 5 suggest poor performance.

How does the Synthego CRISPR Design Tool work?

The tool uses machine learning algorithms trained on experimental data to predict guide RNA efficiency. It considers sequence features, thermodynamics, and potential off-target effects to generate comprehensive scores.

What factors affect guide RNA efficiency?

Key factors include GC content (optimal 40-60%), position-specific nucleotide preferences, thermodynamic stability, secondary structure formation, and PAM accessibility.

Should I consider off-target effects in my design?

Yes, off-target analysis is crucial for ensuring specificity. High-scoring guides with potential off-targets may cause unintended edits, so balance efficiency with specificity.

What PAM sequence should I use for my CRISPR experiment?

NGG is the most common PAM for SpCas9 and offers good targeting flexibility. Alternative Cas proteins like Cpf1 (TTTN PAM) or SaCas9 (NNGRRT PAM) can access different genomic sites.

How long should my guide RNA sequence be?

Standard guide RNAs are typically 20 nucleotides long, though 19-23 nucleotides can work. The length affects both efficiency and specificity, with 20 nt being optimal for most applications.

Can I validate my CRISPR guide RNA design experimentally?

Yes, computational predictions should be validated through in vitro or in vivo experiments. Test multiple predicted high-efficiency guides to confirm performance in your specific system.

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